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Does the Internet Still Demonstrate Fractal Nature?

机译:互联网是否仍显示分形性质?

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The self-similar nature of bursty Internet traffic has been investigated for the last decade. A first generation of papers, approximately from 1994 to 2004, argued that the traditionally used Poisson models oversimplified the characteristics of network traffic and were not appropriate for modeling bursty, local-area, and wide-area network traffic. Since 2004, a second generation of papers has challenged the suitability of these results in networks of the new century and has claimed that the traditional Poisson-based and other models are still more appropriate for characterizing todaypsilas Internet traffic. A possible explanation was that as the speed and amount of Internet traffic grow spectacularly, any irregularity of the network traffic, such as self-similarity, might cancel out as a consequence of high-speed optical connections, new communications protocols, and the vast number of multiplexed flows. These papers analyzed traffic traces of Internet backbone collected in 2003. In one of our previous papers we applied the theory of smoothly truncated Levy flights and the linear fractal model in examining the variability of Internet traffic from self-similar to Poisson. We demonstrated that the series of interarrival times was still close to a self-similar process, but the burstiness of the packet lengths decreased significantly compared to earlier traces. Since then, new traffic traces have been made public, including ones captured from the Internet backbone in 2008. In this paper we analyze these traffic traces and apply our new analytical methods to illustrate the tendency of Internet traffic burstiness. Ultimately, we attempt to answer the question: Does the Internet still demonstrate fractal nature?
机译:在过去的十年中,研究了突发互联网流量的自相似性质。第一代论文(大约从1994年到2004年)认为,传统上使用的Poisson模型过分简化了网络流量的特征,不适用于对突发性,局域和广域网络流量进行建模。自2004年以来,第二代论文就这些结果在新世纪网络中的适用性提出了挑战,并声称传统的基于Poisson的模型和其他模型仍然更适合表征当今的互联网流量。可能的解释是,随着Internet流量的速度和数量惊人地增长,由于高速光连接,新的通信协议以及数量众多,网络流量的任何不规则性(例如自相似性)都可能被抵消。多路复用流。这些论文分析了2003年收集的Internet骨干网的流量痕迹。在我们以前的一篇论文中,我们应用了平滑截断的Levy飞行理论和线性分形模型来研究Internet流量从自相似到Poisson的变异性。我们证明了到达间隔的时间序列仍接近自相似过程,但是与早期轨迹相比,数据包长度的突发性显着降低。从那时起,新的流量跟踪已公开,包括从2008年从Internet骨干中捕获的流量跟踪。在本文中,我们对这些流量跟踪进行了分析,并应用新的分析方法来说明Internet流量突发性的趋势。最终,我们尝试回答以下问题:Internet是否仍显示分形性质?

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